SWARM-BOTS Sintesi della relazione

Algorithms for path formation in a swarm of robots

S-bots have rather limited visual capabilities and can perceive coloured objects at a maximum distance of 40cm. In order to be able to retrieve an object they first have to find it. Then, in order to facilitate the retrieval task, they build a path connecting the object to the target location. This path can be exploited by other s-bots or by a swarm-bot to find the way to the object and then back to the target location.

The exploratory strategy employed by the s-bots takes inspiration from the path formation behaviour of ants. Ants deposit pheromones on the ground while walking and this gives raise to paths shared at the colony level. As our s-bots cannot deposit pheromones, they build visual paths as follows. They start from the target location identified by a blue object and randomly explore the space around it. When they reach a maximum distance from the target location they become beacons of the forming visual path. This means they stop moving and turn on their light. Other s-bots continue the random search around the beacon and can become beacons themselves extending in this way the visual path. The direction of growth of the visual path is therefore random and is not guaranteed to reach the object to be retrieved. However, visual paths under formation have some probability of dissolving and therefore unsuccessful searches (that is, incomplete visual paths that do not reach the object to be retrieved) can restart until a complete visual path is constructed. Once this stochastic procedure finds a visual path connecting the target location to the object to be retrieved, the visual path can be exploited by the s-bots to reach the target location and then to retrieve the object. The main advantage of this exploration strategy is that it relies on local information and simple rules and does not require the s-bots to create a map-like representation of the world.

We have conducted a series of experiments that aims to reveal the effect of two probabilistic control parameters on the exploration strategies. The two parameters define the probability of a chain member to become an explorer, and the probability of an explorer to become a chain member. Our studies focused on the shape of the formed chains and the speed of the chain formation process while varying the two parameters. Generally speaking, we have shown that by varying parameters of the s-bots controller it is possible to generate a variety of exploration strategies. By manipulating a control specific parameter, that is the explorer timeout, is enough to obtain different shapes of the formed chains and different speeds of the chain formation process. In particular, two different behaviours can be observed: while a short explorer timeout leads to the fast formation of many chains, a long explorer timeout results in the slow formation of fewer chains.

In another series of experiments we have compared the effectiveness of two different strategies with respect to their capacity to adapt to the characteristics of the environment. In the simpler strategy, we have static visual paths: the s-bots beacons do not move. In the other setup, the s-bots that form a visual path move in a coordinated way without breaking the path. The controllers developed in simulation have been ported successfully on the real s-bots that proved capable of finding the object and building a chain connecting the latter to the target location. The time required to build the chain is a function of the complexity of the environment and in particular depends on the presence, or absence, of obstacles.